dipy_fit_sfm

Synopsis

Workflow for Sparse Fascicle Model (SFM)

See [1] for further details about the method.

Usage

dipy_fit_sfm [OPTIONS] input_files bvalues_files bvectors_files mask_files

Input Parameters

• input_files

  Path to the input volumes. This path may contain wildcards to

• bvalues_files

  Path to the bvalues files. This path may contain wildcards to use multiple bvalues files at once.

• bvectors_files

  Path to the bvalues files. This path may contain wildcards to use

• mask_files

  Path to the input masks. This path may contain wildcards to use

General Options

• --sphere_name

  Sphere name on which to reconstruct the fODFs. (default: None)

• --response

  Response function to use. If None, the response function will be defined automatically. (default: None)

• --solver

  This will determine the algorithm used to solve the set of linear equations underlying this model. It needs to be one of the following: {‘ElasticNet’, ‘NNLS’} (default: ElasticNet)

• --l1_ratio

  The ElasticNet mixing parameter, with 0 <= l1_ratio <= 1. For l1_ratio = 0 the penalty is an L2 penalty. For l1_ratio = 1 it is an L1 penalty. For 0 < l1_ratio < 1, the penalty is a combination of L1 and L2. (default: 0.5)

• --alpha

  Sets the balance between least-squares error and L1/L2 regularization in ElasticNet :footcite:p`Zou2005`. (default: 0.001)

• --seed

  Seed for the random number generator. (default: 42)

• --b0_threshold

  Threshold used to find b0 volumes. (default: 50.0)

• --bvecs_tol

  Bvecs should be unit vectors. (default: 0.01)

• --sh_order_max

  Maximum spherical harmonics order (l) used in the SFM fit. (default: 8)

• --relative_peak_threshold

  Only return peaks greater than relative_peak_threshold * m where m is the largest peak. (default: 0.5)

• --min_separation_angle

  The angle tolerance between directions. (default: 25)

• --parallel

  Whether to use parallelization in peak-finding. (default: False)

• --extract_pam_values

  Save or not to save pam volumes as single nifti files. (default: False)

• --num_processes

  If parallel is True, the number of subprocesses to use (default: None)

Output Options

• --out_dir

  Output directory. (default: current directory)

• --out_pam

  Name of the peaks volume to be saved. (default: peaks.pam5)

• --out_shm

  Name of the spherical harmonics volume to be saved. (default: shm.nii.gz)

• --out_peaks_dir

  Name of the peaks directions volume to be saved. (default: peaks_dirs.nii.gz)

• --out_peaks_values

  Name of the peaks values volume to be saved. (default: peaks_values.nii.gz)

• --out_peaks_indices

  Name of the peaks indices volume to be saved. (default: peaks_indices.nii.gz)

• --out_gfa

  Name of the generalized FA volume to be saved. (default: gfa.nii.gz)

• --out_sphere

  Sphere vertices name to be saved. (default: sphere.txt)

• --out_b

  Name of the B Matrix to be saved. (default: B.nii.gz)

• --out_qa

  Name of the Quantitative Anisotropy to be saved. (default: qa.nii.gz)

References

[1]

Ariel Rokem, Jason D. Yeatman, Franco Pestilli, Kendrick N. Kay, Aviv Mezer, Stefan van der Walt, and Brian A. Wandell. Evaluating the Accuracy of Diffusion MRI Models in White Matter. PLOS ONE, 10(4):1–26, April 2015. URL: https://doi.org/10.1371/journal.pone.0123272, doi:10.1371/journal.pone.0123272.

Garyfallidis, E., M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, and I. Nimmo-Smith. Dipy, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, 1-18, 2014.